Get the verified free-tier limit of an AI tool: how far the allowance goes, what happens at the wall, the official source page, and the date it was checked. Absence of a tool means no officially verifiable number exists — this dataset publishes no unsourced figures.
| Name | Required | Description | Default |
|---|---|---|---|
| lang | No | Data language, default en | |
| tool | Yes | Tool slug (e.g. "kimi") or name |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description takes on the burden of behavioral disclosure. It explains the output content (source, date, allowance details), the absence behavior, and the data quality policy ('publishes no unsourced figures'). This goes beyond a basic read operation, though it does not mention side effects or error conditions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the primary purpose, then expanding into result details and a usage caveat. Every sentence earns its place with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 params, no output schema), the description thoroughly covers what the tool returns, how to interpret the absence of results, and the verification policy. This is complete for a lookup tool and compensates for the lack of an output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already fully describes both parameters (tool slug/name and lang enum with default). The description does not add parameter-specific guidance, but with 100% schema coverage, the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get') and clearly identifies the resource ('verified free-tier limit of an AI tool'), listing concrete return items (allowance extent, wall behavior, source page, check date). It distinguishes itself from sibling tools like check_commercial_use and search_ai_tools by focusing on free-tier limits and verification.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context: retrieving verified free-tier allowance details for an AI tool. It also provides guidance on interpreting absence results ('Absence of a tool means no officially verifiable number exists'). It does not explicitly name alternatives, but the sibling tool names make differentiation clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Each tool targets a clearly distinct task: querying limits, checking commercial use, fact-checking claims, comparing categories, searching the directory, auditing stacks, building workflows, and monitoring changes. Even the two change-related tools are differentiated by one being a query and the other a subscription.
All tool names follow a consistent lowercase snake_case verb_noun pattern (audit_, build_, check_, compare_, explain_, find_, get_, search_, watch_). Repeated verbs like check_ and get_ are paired with distinct objects, making the pattern predictable and easy to scan.
At 14 tools, the set is well-scoped for the breadth of the domain (verifying free tiers, checking commercial use, tracking changes, building workflows, and China-specific rules). Each tool earns its place without redundancy, fitting comfortably within the ideal range.
The surface covers the full lifecycle: querying a single tool's limit, comparing across categories, searching the directory, fact-checking claims, explaining missing data, finding alternatives, auditing a stack, calculating quota fit, and both reading and subscribing to changes. No obvious dead ends or missing operations for the stated purpose.